Further information is available on these particular topics:
Data sharing and preservation enables researchers to utilize an existing dataset to replicate research results or conduct new research. Items required for a data management plan will vary by the type of research. The following list is not exhaustive, and not all items will be required for each project. Some data repositories have specific file formats and requirements for storage.
When quantitative, data should be preserved in a format widely accessible or convertible across software platforms. Delimited text files are ideal, as are data files for common statistical packages, but widely employed formats like Microsoft Excel spreadsheets may also be acceptable. When qualitative, data should also be in a widely readable format. In both cases, inventory the files and their contents.
Include any code used to transform raw data into the final format used for analysis. Also include any code used to perform the data analysis.
A codebook will contain the array of responses for each variable, as well as a history of all conversions or alterations.
When data is originally generated, provide the instruments of data production. These may take the form of surveys, experimental design procedures, and other similar documents.
In cases where mathematical models or procedures are codified in academic papers, include these.
Include any consent agreements that are used to produce the sample.
Unless otherwise specified on this page, this work is licensed under a
Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.